Is it possible to create a Dispatcher for the current thread? Check this sample code as an example of what I want to accomplish:
val dispatcher = if (parallel) {
Dispatcher.Default
} else {
// What should I write here so I just use the current thread to run doStuff?
}
val deferredList = list.map {
async(dispatcher) { doStuff(it) }
}
When you build a coroutine, you're passing a CoroutineContext as argument. If you don't pass anything, the new coroutine is built with the current CoroutineContext (its parent's context).
Instead of a Dispatcher you should aim to a CoroutineContext:
val context = if (parallel) {
Dispatchers.Default
} else {
coroutineContext
}
val deferredList = list.map {
async(context) { doStuff(it) }
}
You can also "extract" every Element of the context individually using the Element type as key:
Job: coroutineContext[Job]
Dispatcher: coroutineContext[ContinuationInterceptor]
ExceptionHandler: coroutineContext[CoroutineExceptionHandler]
Name: coroutineContext[CoroutineName]
Use Dispatchers.Unconfined, it's used exactly to run on a current thread.
The whole code will look as follows:
val dispatcher = if (parallel) Dispatcher.Default else Dispatchers.Unconfined
val deferredList = list.map {
async(dispatcher) { doStuff(it) }
}
I'm trying to find the best way to run a Task from a dedicated background thread.
The context of usage is consuming from a Kafka topic and raising an async event handler to handle the ConsumeResult<TKey, TValue> instance.
A Kafka Consumer (the consumer instance below) blocks the thread until a message is consumed or the CancellationToken it is passed has been cancelled.
consumeThread = new Thread(Consume)
{
Name = "Kafka Consumer Thread",
IsBackground = true,
};
This is the implementation of the Consume method I came up with, which is started by the dedicated thread above:
private void Consume(object _)
{
try
{
while (!cancellationTokenSource.IsCancellationRequested)
{
var consumeResult = consumer.Consume(cancellationTokenSource.Token);
var consumeResultEventArgs = new ConsumeResultReceivedEventArgs<TKey, TValue>(
consumer, consumeResult, cancellationTokenSource.Token);
_ = Task.Run(async () =>
{
if (onConsumeResultReceived is null) continue;
var handlerInstances = onConsumeResultReceived.GetInvocationList();
foreach (ConsumeResultReceivedEventHandler<TKey, TValue> handlerInstance in handlerInstances)
{
if (cancellationTokenSource.IsCancellationRequested) return;
await handlerInstance(this, consumeResultEventArgs).ConfigureAwait(false);
}
}, cancellationTokenSource.Token);
}
}
catch (OperationCanceledException)
{
}
catch (ThreadInterruptedException)
{
}
catch (ThreadAbortException)
{
// Aborting a thread is not implemented in .NET Core.
}
}
I'm not sure this is the recommened way to run a Task from a dedicated Thread, so any advice would be very much appreciated.
It's not clear to me why you need a dedicated thread at all. The code as it currently stands starts a thread and then that thread blocks for consumption and then raises the event handler on a thread pool thread.
The _ = Task.Run idiom is a "fire and forget", which is dangerous in the sense that it will silently swallow any exceptions from your event raising code or event handlers.
I'd recommend replacing Thread with Task.Run, and just raising the event handlers directly:
consumeTask = Task.Run(ConsumeAsync);
private async Task ConsumeAsync()
{
while (true)
{
var consumeResult = consumer.Consume(cancellationTokenSource.Token);
var consumeResultEventArgs = new ConsumeResultReceivedEventArgs<TKey, TValue>(
consumer, consumeResult, cancellationTokenSource.Token);
if (onConsumeResultReceived is null) continue;
var handlerInstances = onConsumeResultReceived.GetInvocationList();
foreach (ConsumeResultReceivedEventHandler<TKey, TValue> handlerInstance in handlerInstances)
{
if (cancellationTokenSource.IsCancellationRequested) return;
await handlerInstance(this, consumeResultEventArgs).ConfigureAwait(false);
}
}
}
First of all, I'm new in Kotlin, so please be nice :).
It's also my first time posting on StackOverflow
I want to literally STOP the current thread that I created but nothing works.
I tried quit(), quitSafely(), interrupt() but nothing works.
I created a class (Data.kt), in which I create and initialize a Handler and HandlerThread as follows :
class Dispatch(private val label: String = "main") {
var handler: Handler? = null
var handlerThread: HandlerThread? = null
init {
if (label == "main") {
handlerThread = null
handler = Handler(Looper.getMainLooper())
} else {
handlerThread = HandlerThread(label)
handlerThread!!.start()
handler = Handler(handlerThread!!.looper)
}
}
fun async(runnable: Runnable) = handler!!.post(runnable)
fun async(block: () -> (Unit)) = handler!!.post(block)
fun asyncAfter(milliseconds: Long, function: () -> (Unit)) {
handler!!.postDelayed(function, milliseconds)
}
fun asyncAfter(milliseconds: Long, runnable: Runnable) {
handler!!.postDelayed(runnable, milliseconds)
}
companion object {
val main = Dispatch()
private val global = Dispatch("global")
//fun global() = global
}
}
And now, in my DataManager, I use these to do asynchronous things :
fun getSomething(forceNetwork: Boolean ) {
val queue1 = Dispatch("thread1") // Create a thread called "thread1"
queue1.async {
for (i in 0..2_000_000) {
print("Hello World")
// Do everything i want in the current thread
}
// And on the main thread I call my callback
Dispatch.main.async {
//callback?.invoke(.........)
}
}
}
Now, in my MainActivity, I made 2 buttons :
One for running the function getSomething()
The other one is used for switching to another Controller View :
val button = findViewById<Button>(R.id.button)
button.setOnClickListener {
DataManager.getSomething(true)
}
val button2 = findViewById<Button>(R.id.button2)
button2.setOnClickListener {
val intent = Intent(this, Test::class.java) // Switch to my Test Controller
intent.setFlags(Intent.FLAG_ACTIVITY_NO_HISTORY)
startActivity(intent)
finish()
}
Is there a way to stop the thread, because when I switch to my second View, print("Hello World") is still triggered, unfortunately.
Thanks for helping me guys I hope that you understand !
A thread needs to periodically check a (global) flag and when it becomes true then the thread will break out from the loop. Java threads cannot be safely stopped without its consent.
Refer to page 252 here http://www.rjspm.com/PDF/JavaTheCompleteReference.pdf that describes the true story behind the legend.
I think that a truly interruptible thread is only possible through the support of the operating system kernel. The actual true lock is held deep down by the CPU hardware microprocessor.
I've got a Sequence (from File.walkTopDown) and I need to run a long-running operation on each of them. I'd like to use Kotlin best practices / coroutines, but I either get no parallelism, or way too much parallelism and hit a "too many open files" IO error.
File("/Users/me/Pictures/").walkTopDown()
.onFail { file, ex -> println("ERROR: $file caused $ex") }
.filter { ... only big images... }
.map { file ->
async { // I *think* I want async and not "launch"...
ImageProcessor.fromFile(file)
}
}
This doesn't seem to run it in parallel, and my multi-core CPU never goes above 1 CPU's worth. Is there a way with coroutines to run "NumberOfCores parallel operations" worth of Deferred jobs?
I looked at Multithreading using Kotlin Coroutines which first creates ALL the jobs then joins them, but that means completing the Sequence/file tree walk completly bfore the heavy processing join step, and that seems... iffy! Splitting it into a collect and a process step means the collection could run way ahead of the processing.
val jobs = ... the Sequence above...
.toSet()
println("Found ${jobs.size}")
jobs.forEach { it.await() }
This isn't specific to your problem, but it does answer the question of, "how to cap kotlin coroutines maximum concurrency".
EDIT: As of kotlinx.coroutines 1.6.0 (https://github.com/Kotlin/kotlinx.coroutines/issues/2919), you can use limitedParallelism, e.g. Dispatchers.IO.limitedParallelism(123).
Old solution: I thought to use newFixedThreadPoolContext at first, but 1) it's deprecated and 2) it would use threads and I don't think that's necessary or desirable (same with Executors.newFixedThreadPool().asCoroutineDispatcher()). This solution might have flaws I'm not aware of by using Semaphore, but it's very simple:
import kotlinx.coroutines.async
import kotlinx.coroutines.awaitAll
import kotlinx.coroutines.coroutineScope
import kotlinx.coroutines.sync.Semaphore
import kotlinx.coroutines.sync.withPermit
/**
* Maps the inputs using [transform] at most [maxConcurrency] at a time until all Jobs are done.
*/
suspend fun <TInput, TOutput> Iterable<TInput>.mapConcurrently(
maxConcurrency: Int,
transform: suspend (TInput) -> TOutput,
) = coroutineScope {
val gate = Semaphore(maxConcurrency)
this#mapConcurrently.map {
async {
gate.withPermit {
transform(it)
}
}
}.awaitAll()
}
Tests (apologies, it uses Spek, hamcrest, and kotlin test):
import kotlinx.coroutines.ExperimentalCoroutinesApi
import kotlinx.coroutines.delay
import kotlinx.coroutines.launch
import kotlinx.coroutines.runBlocking
import kotlinx.coroutines.test.TestCoroutineDispatcher
import org.hamcrest.MatcherAssert.assertThat
import org.hamcrest.Matchers.greaterThanOrEqualTo
import org.hamcrest.Matchers.lessThanOrEqualTo
import org.spekframework.spek2.Spek
import org.spekframework.spek2.style.specification.describe
import java.util.concurrent.atomic.AtomicInteger
import kotlin.test.assertEquals
#OptIn(ExperimentalCoroutinesApi::class)
object AsyncHelpersKtTest : Spek({
val actionDelay: Long = 1_000 // arbitrary; obvious if non-test dispatcher is used on accident
val testDispatcher = TestCoroutineDispatcher()
afterEachTest {
// Clean up the TestCoroutineDispatcher to make sure no other work is running.
testDispatcher.cleanupTestCoroutines()
}
describe("mapConcurrently") {
it("should run all inputs concurrently if maxConcurrency >= size") {
val concurrentJobCounter = AtomicInteger(0)
val inputs = IntRange(1, 2).toList()
val maxConcurrency = inputs.size
// https://github.com/Kotlin/kotlinx.coroutines/issues/1266 has useful info & examples
runBlocking(testDispatcher) {
print("start runBlocking $coroutineContext\n")
// We have to run this async so that the code afterwards can advance the virtual clock
val job = launch {
testDispatcher.pauseDispatcher {
val result = inputs.mapConcurrently(maxConcurrency) {
print("action $it $coroutineContext\n")
// Sanity check that we never run more in parallel than max
assertThat(concurrentJobCounter.addAndGet(1), lessThanOrEqualTo(maxConcurrency))
// Allow for virtual clock adjustment
delay(actionDelay)
// Sanity check that we never run more in parallel than max
assertThat(concurrentJobCounter.getAndAdd(-1), lessThanOrEqualTo(maxConcurrency))
print("action $it after delay $coroutineContext\n")
it
}
// Order is not guaranteed, thus a Set
assertEquals(inputs.toSet(), result.toSet())
print("end mapConcurrently $coroutineContext\n")
}
}
print("before advanceTime $coroutineContext\n")
// Start the coroutines
testDispatcher.advanceTimeBy(0)
assertEquals(inputs.size, concurrentJobCounter.get(), "All jobs should have been started")
testDispatcher.advanceTimeBy(actionDelay)
print("after advanceTime $coroutineContext\n")
assertEquals(0, concurrentJobCounter.get(), "All jobs should have finished")
job.join()
}
}
it("should run one at a time if maxConcurrency = 1") {
val concurrentJobCounter = AtomicInteger(0)
val inputs = IntRange(1, 2).toList()
val maxConcurrency = 1
runBlocking(testDispatcher) {
val job = launch {
testDispatcher.pauseDispatcher {
inputs.mapConcurrently(maxConcurrency) {
assertThat(concurrentJobCounter.addAndGet(1), lessThanOrEqualTo(maxConcurrency))
delay(actionDelay)
assertThat(concurrentJobCounter.getAndAdd(-1), lessThanOrEqualTo(maxConcurrency))
it
}
}
}
testDispatcher.advanceTimeBy(0)
assertEquals(1, concurrentJobCounter.get(), "Only one job should have started")
val elapsedTime = testDispatcher.advanceUntilIdle()
print("elapsedTime=$elapsedTime")
assertThat(
"Virtual time should be at least as long as if all jobs ran sequentially",
elapsedTime,
greaterThanOrEqualTo(actionDelay * inputs.size)
)
job.join()
}
}
it("should handle cancellation") {
val jobCounter = AtomicInteger(0)
val inputs = IntRange(1, 2).toList()
val maxConcurrency = 1
runBlocking(testDispatcher) {
val job = launch {
testDispatcher.pauseDispatcher {
inputs.mapConcurrently(maxConcurrency) {
jobCounter.addAndGet(1)
delay(actionDelay)
it
}
}
}
testDispatcher.advanceTimeBy(0)
assertEquals(1, jobCounter.get(), "Only one job should have started")
job.cancel()
testDispatcher.advanceUntilIdle()
assertEquals(1, jobCounter.get(), "Only one job should have run")
job.join()
}
}
}
})
Per https://play.kotlinlang.org/hands-on/Introduction%20to%20Coroutines%20and%20Channels/09_Testing, you may also need to adjust compiler args for the tests to run:
compileTestKotlin {
kotlinOptions {
// Needed for runBlocking test coroutine dispatcher?
freeCompilerArgs += "-Xuse-experimental=kotlin.Experimental"
freeCompilerArgs += "-Xopt-in=kotlin.RequiresOptIn"
}
}
testImplementation 'org.jetbrains.kotlinx:kotlinx-coroutines-test:1.4.1'
The problem with your first snippet is that it doesn't run at all - remember, Sequence is lazy, and you have to use a terminal operation such as toSet() or forEach(). Additionally, you need to limit the number of threads that can be used for that task via constructing a newFixedThreadPoolContext context and using it in async:
val pictureContext = newFixedThreadPoolContext(nThreads = 10, name = "reading pictures in parallel")
File("/Users/me/Pictures/").walkTopDown()
.onFail { file, ex -> println("ERROR: $file caused $ex") }
.filter { ... only big images... }
.map { file ->
async(pictureContext) {
ImageProcessor.fromFile(file)
}
}
.toList()
.forEach { it.await() }
Edit:
You have to use a terminal operator (toList) befor awaiting the results
I got it working with a Channel. But maybe I'm being redundant with your way?
val pipe = ArrayChannel<Deferred<ImageFile>>(20)
launch {
while (!(pipe.isEmpty && pipe.isClosedForSend)) {
imageFiles.add(pipe.receive().await())
}
println("pipe closed")
}
File("/Users/me/").walkTopDown()
.onFail { file, ex -> println("ERROR: $file caused $ex") }
.forEach { pipe.send(async { ImageFile.fromFile(it) }) }
pipe.close()
This doesn't preserve the order of the projection but otherwise limits the throughput to at most maxDegreeOfParallelism. Expand and extend as you see fit.
suspend fun <TInput, TOutput> (Collection<TInput>).inParallel(
maxDegreeOfParallelism: Int,
action: suspend CoroutineScope.(input: TInput) -> TOutput
): Iterable<TOutput> = coroutineScope {
val list = this#inParallel
if (list.isEmpty())
return#coroutineScope listOf<TOutput>()
val brake = Channel<Unit>(maxDegreeOfParallelism)
val output = Channel<TOutput>()
val counter = AtomicInteger(0)
this.launch {
repeat(maxDegreeOfParallelism) {
brake.send(Unit)
}
for (input in list) {
val task = this.async {
action(input)
}
this.launch {
val result = task.await()
output.send(result)
val completed = counter.incrementAndGet()
if (completed == list.size) {
output.close()
} else brake.send(Unit)
}
brake.receive()
}
}
val results = mutableListOf<TOutput>()
for (item in output) {
results.add(item)
}
return#coroutineScope results
}
Example usage:
val output = listOf(1, 2, 3).inParallel(2) {
it + 1
} // Note that output may not be in same order as list.
Why not use the asFlow() operator and then use flatMapMerge?
someCoroutineScope.launch(Dispatchers.Default) {
File("/Users/me/Pictures/").walkTopDown()
.asFlow()
.filter { ... only big images... }
.flatMapMerge(concurrencyLimit) { file ->
flow {
emit(runInterruptable { ImageProcessor.fromFile(file) })
}
}.catch { ... }
.collect()
}
Then you can limit the simultaneous open files while still processing them concurrently.
To limit the parallelism to some value there is limitedParallelism function starting from the 1.6.0 version of the kotlinx.coroutines library. It can be called on CoroutineDispatcher object. So to limit threads for parallel execution we can write something like:
val parallelismLimit = Runtime.getRuntime().availableProcessors()
val limitedDispatcher = Dispatchers.Default.limitedParallelism(parallelismLimit)
val scope = CoroutineScope(limitedDispatcher) // we can set limitedDispatcher for the whole scope
scope.launch { // or we can set limitedDispatcher for a coroutine launch(limitedDispatcher)
File("/Users/me/Pictures/").walkTopDown()
.onFail { file, ex -> println("ERROR: $file caused $ex") }
.filter { ... only big images... }
.map { file ->
async {
ImageProcessor.fromFile(file)
}
}.toList().awaitAll()
}
ImageProcessor.fromFile(file) will be executed in parallel using parallelismLimit number of threads.
This will cap coroutines to workers. I'd recommend watching https://www.youtube.com/watch?v=3WGM-_MnPQA
package com.example.workers
import kotlinx.coroutines.*
import kotlinx.coroutines.channels.ReceiveChannel
import kotlinx.coroutines.channels.produce
import kotlin.system.measureTimeMillis
class ChannellibgradleApplication
fun main(args: Array<String>) {
var myList = mutableListOf<Int>(3000,1200,1400,3000,1200,1400,3000)
runBlocking {
var myChannel = produce(CoroutineName("MyInts")) {
myList.forEach { send(it) }
}
println("Starting coroutineScope ")
var time = measureTimeMillis {
coroutineScope {
var workers = 2
repeat(workers)
{
launch(CoroutineName("Sleep 1")) { theHardWork(myChannel) }
}
}
}
println("Ending coroutineScope $time ms")
}
}
suspend fun theHardWork(channel : ReceiveChannel<Int>)
{
for(m in channel) {
println("Starting Sleep $m")
delay(m.toLong())
println("Ending Sleep $m")
}
}
I'm working on a command line program in Scala. Some of the commands will spawn background thread to perform some work. Some commands will spawn threads that will run the same task repetitively with some delay. I also need a stop command that will prevent existing background task from repeating (doesn't need to kill it, just quit after finishing the iteration). What are the best primitives to construct this sort of program?
I'm thinking about using Futures, e.g. below. What do you guys think of this design? How would you implement this sort of functionality?
case class OneTimeTaskCommand(arg: String)
case class StopTaskCommand(name: String)
case class RepeatingTaskCommand(name: String, delay: Long, arg: String)
def runOneTimeTask(arg: String): Unit = { ... }
def runRepeatingTaskCommand(arg: String): Unit = { ... }
trait Scheduler {
def schedule(name: String, delay: Long): Unit
def unschedule(name: String): Unit
def isScheduled(name: String): Boolean = repeatDelay(name).isDefined
def repeatDelay(name: String): Option[Long]
}
def runCommand(command)(implicit scheduler: Scheduler): Future[Unit] = {
command match {
case OneTimeTaskCommand(arg) => Future(runOneTimeTask(arg))
case StopTaskCommand(name) =>
if (scheduler.isScheduled(name)) {
scheduler.unschedule(name)
Future.successful(())
} else {
Future.failure(new CommandException(s"task $name is not running"))
}
case RepeatingTaskCommand(name, delay, arg) =>
/* function to generate repeating future */
def createFuture(): Future[Unit] = {
runRepeatingTaskCommand(arg)).flatMap { _ =>
scheduler.repeatDelay(name) match {
case Some(d) =>
Thread.sleep(d)
Future(createFuture())
case None =>
Future.successful(())
}
}
}
/* spin off repeating task */
if (scheduler.isScheduled(name)) {
Future.failure(new CommandException(s"task $name is already running"))
} else {
scheduler.schedule(name, delay)
createFuture()
}
}
}
The code above will be integrated into some REPL that reads users input and invokes some of the following calls:
implicit val scheduler: Scheduler = new SchedulerImpl
runCommand(OneTimeTaskCommand(someArg))
// Run backgrounded task to be repeated every second
runCommand(RepeatingTaskCommand("backgrounded-task", 1000L, someArg))
// Stop backgrounded task
runCommand(StopTaskCommand("backgrounded-task"))